Triple
T38541774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peroni (in certain markets) |
E924850
|
entity |
| Predicate | hasCountryOfOriginStyle |
P59353
|
FINISHED |
| Object | Italy |
E863
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Italy | Statement: [Peroni (in certain markets), hasCountryOfOriginStyle, Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountryOfOriginStyle Context triple: [Peroni (in certain markets), hasCountryOfOriginStyle, Italy]
-
A.
originCountryStyle
chosen
Indicates that something is characterized by or created in the style or manner typical of a particular country of origin.
-
B.
countryOfOrigin
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
C.
brandOriginContext
Indicates the contextual relationship between a brand and the place, culture, or circumstances from which it originates.
-
D.
composerCountryOfOrigin
Indicates the country from which a composer originally comes or with which they are primarily culturally or nationally associated.
-
E.
namedAfterCountryOfOrigin
Indicates that an entity is named after the country from which it originates or was first produced.
- F. None of above.
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76eadeac081909cdfdd0474cb6765 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41e032f1a08190b2453081e03d9f6c |
completed | June 29, 2026, 3:02 a.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.